Automated Machine Learning in Action

Author:   Qingquan Song ,  Haifeng Jin ,  Xia Hu
Publisher:   Manning Publications
ISBN:  

9781617298059


Pages:   300
Publication Date:   01 June 2022
Format:   Paperback
Availability:   Not yet available   Availability explained
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Automated Machine Learning in Action


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Overview

Optimize every stage of your machine learning pipelines with powerful automation components and cutting-edge tools like AutoKeras and KerasTuner. Automated Machine Learning in Action, filled with hands-onexamples and written in an accessible style, reveals how premade machine learning components can automate time-consuming ML tasks. Automated Machine Learning in Action teaches you to automate selecting the best machine learning models or data preparation methods for your own machine learning tasks, so your pipelines tune themselves without needing constant input. You'll quickly run through machine learning basics thatopen upon AutoML to non-data scientists, before putting AutoML into practicefor image classification, supervised learning, and more. Automated machine learning (AutoML) automates complex andtime-consuming stages in a machine learning pipeline with pre packaged optimal solutions. This frees up data scientists from data processing and manualtuning, and lets domain experts easily apply machine learning models to their projects.

Full Product Details

Author:   Qingquan Song ,  Haifeng Jin ,  Xia Hu
Publisher:   Manning Publications
Imprint:   Manning Publications
Dimensions:   Width: 18.60cm , Height: 2.20cm , Length: 23.40cm
Weight:   0.620kg
ISBN:  

9781617298059


ISBN 10:   1617298050
Pages:   300
Publication Date:   01 June 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

Reviews

Automating automation itself is a new concept and this book does justice to it in terms of explaining the concepts, sharing real world advancements, use cases and research related to the topic. Satej KumarSahu A book with a lot of promise, covering a topic that's like to become hot in the next year or so. Read this now, and get ahead of the curve! RichardVaughan A nice introduction to AutoML, its ambitions, and challenges bothin theory and in practice. Alain Couniot Helps you to clearly understand the process of Machine Learning automation. The examples are clear, concise, and applicable to the real world. Walter Alexander Mata Lopez The author's friendly style makes novices feel ready to try outAutoML tools. Gaurav Kumar Leekha A great book to take your machine learning skills to the next level. Harsh Raval An impressive effort by the authors to break down a complex MLtopic into understandable chunks. Venkatesh Rajagopal


Author Information

Qingquan Song, Haifeng Jin, and Dr. Xia “Ben” Hu are the creators of the AutoKeras automated deep learning library. Qingquan and Haifeng are PhD students at Texas A&M University, and have both published papers at major data mining conferences and journals. Dr. Hu is an associate professor at Texas A&M University in the Department of Computer Science and Engineering, whose work has been utilized by TensorFlow, Apple, and Bing.

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